Mortality, Cardiovascular Disease, and Their Associations With Risk Factors in Southeast Asia

Background The drivers of cardiovascular disease (CVD) and all-cause mortality may differ around the world. Regional-level prospective data can help guide policies to reduce CVD and all-cause mortality. Objectives This study examined the incidence of CVD and mortality in Malaysia and the Philippines and estimated the population-level risks attributable to common risk factors for each outcome. Methods This prospective cohort study included 20,272 participants from Malaysia and the Philippines. The mean follow-up was 8.2 years. The incidences of CVD and mortality rates were calculated for the overall cohort and in key subgroups. For each outcome, population-attributable fractions (PAFs) were calculated to compare risks associated with 12 modifiable risk factors. Results The mean age of the cohort was 51.8 years (59% women). Leading causes of mortality were CVD (37.9%) and cancer (12.4%). The incidence of CVD (per 1,000 person-years) was higher in the Philippines (11.0) than Malaysia (8.3), and CVD contributed to a higher proportion of deaths in the Philippines (58% vs 36%). By contrast, all-cause mortality rates were higher in Malaysia (14.1) than in the Philippines (10.9). Approximately 78% of the PAF for CVD and 68% of the PAF for all-cause mortality were attributable to 12 modifiable risk factors. For CVD, the largest PAF was from hypertension (24.2%), whereas for all-cause mortality, the largest PAF was from low education (18.4%). Conclusions CVD and cancer account for one-half of adult mortality in Malaysia and the Philippines. Hypertension was the largest population driver of CVD, whereas low education was associated with the largest burden of overall mortality.

T he burden of cardiovascular disease (CVD), all-cause mortality, and their determinants may differ in various countries.Understanding these differences is essential in developing context-specific health policies.Health policies aimed at reducing CVD and all-cause mortality can be better informed from contemporary data on these 2 vital outcomes, to understand their drivers and variation by sex.This can help guide strategies for prevention and treatment within these countries.In particular, there is a lack of prospective data on CVD and all-cause mortality in many countries in Southeast Asia, with existing data largely modeled estimates (eg, from the Global Burden of Disease). 1 Prospective studies can document the incidence rates of CVD and all-cause mortality and clarify the contribution of risk factors.A standardized cohort of participants from countries within Southeast Asia can provide necessary information on whether the rates of CVD and all-cause mortality vary, as well as region-specific data on their determinants.Southeast Asian countries are often analyzed as a homogenous group, even though there are significant differences among many of these countries.For instance, there is a wide variation in religion or culture and government within the region that may affect the risk factor profile and outcomes in an individual country.
Malaysia is a federal constitutional monarchy, with most of its citizens being Sunni Muslims.The Philippines, conversely, is a presidential republic, with 90% of its citizens practicing Christianity. 2e PURE (Prospective Urban Rural Epidemiology) study is a large, community-based study that is evaluating the rates and determinants of CVD and mortality from 27 high-, middle-, and low-income countries.Using standardized methods, we have collected data on a broad range of health determinants and clinical outcomes in participants from 74 communities in Malaysia and the Philippines (2 of the larger countries in the region) during a mean follow-up period of 8.2 years.In this cohort, we aimed to characterize whether CVD incidence and mortality rates varied in key subgroups, by sex and between the 2 countries, and to quantify the contributions of the common modifiable risk factors to these outcomes.

METHODS
STUDY DESIGN AND PARTICIPANTS.PURE is a prospective cohort study of community-based adults aged 35 to 70 years from high-, middle-, and lowincome countries across 6 geographic regions: Asia, Africa, Europe, South America, North America, and the Middle East.The study design has been published previously. 3The present study focuses on DATA COLLECTION.Baseline information was collected using standardized questionnaires and physical measurements.On the basis of their established association with both CVD and mortality shown in our global data, 12 risk factors collected at baseline were evaluated in this analysis. 5The definitions of the risk factors and their thresholds for calculation of Hypertension was defined as a self-reported history of hypertension, a baseline systolic blood pressure $140 mm Hg, a diastolic blood pressure $90 mm Hg, or use of blood pressurelowering medications.Diabetes was defined as a baseline fasting glucose level $126 mg/dL, a selfreported history of diabetes, or treatment with a glucose-lowering agent.Waist and hip circumferences were measured using a standard protocol, and abdominal obesity was defined as a waist-to-hip ratio >0.9 in men and >0.85 in women.Smoking and alcohol use were collected and quantified by selfreport.We used a composite diet score for overall diet quality, which has been replicated in 5 independent cohorts. 6Physical activity was measured using the International Physical Activity Questionnaire. 7Education level was collected as part of the Mortality, CVD, and Risk Factors in Southeast Asia baseline assessment and was chosen as the primary socioeconomic variable of interest because education was found to be a stronger socioeconomic predictor of CVD and mortality than wealth or income in a previous PURE analysis. 8Grip strength was measured by a Jamar dynamometer.Household air pollution was collected at the household level and was defined as the use of kerosene or solid fuels as the primary fuel for cooking.Depression was defined as a score of at least 5 on an 8-symptom score of the Composite International Diagnostic Interview. 9Fasting non-HDL cholesterol was chosen as the primary lipid value of interest because it had the strongest association with CVD in our global risk factor paper.Categories of risk for each risk factor were based on those used in the report on PURE global risk factors. 5is approach allows for consistent thresholds of risk to compare across different regions.Wealth, calculated at the household level, was defined by an index on the basis of ownership of assets and housing characteristics. 8This index has been previously validated in low-, middle-and high-income countries and documented to be a robust measure of wealth, consistent with measures of income and expenditure. 10Participants were categorized into 20 equal groups, on the basis of their wealth percentile, with higher categories denoting greater wealth relative to others from the global cohort in lower-wealth categories.were not implemented at the initiation of the study, or fasting lipids were not collected in a subset of participants.To address this issue, we used multiple imputation for missing data for each risk factor planned for analysis.We used the multiple imputation procedure in SAS software version 9.4 (SAS Institute, Inc), under the assumption that the missing data pattern is random.In particular, the regression-based fully conditional specification method was used in this imputation. 11Five imputed data sets were created for each missing value.Although we did not perform any formal test to check for a missing data mechanism, we do not have adequate information to believe that the missing data pattern is not at random.Estimates are based on the multiple imputation data set and are presented as HRs with 95% CIs.
The PAF estimated the contribution of a risk factor to the development of CVD or to all-cause mortality.
PAFs for each individual or groups of risk factors were estimated using the average PAF approach by Eide and Gefeller 12 and the averisk package in R software (R Foundation) developed by Ferguson et al. 13 Each risk factor of interest was dichotomously categorized based on a prespecified threshold level of risk on the basis of the global PURE report (Supplemental Methods, Supplemental Tables 1 and 2). 5 This approach allows for comparisons with the global PURE data and across different geographic regions.
Average PAF estimates were derived using a mutually adjusted model accounting for all candidate risk factors, age, sex and urban or rural location; where each risk factor was added sequentially to the model in all possible permutations and then the average PAF from these permutations was calculated.In this approach, cumulative PAF estimates for groups of risk factors are additive and cannot exceed 100%.In general, the average PAF method results in smaller PAF estimates for individual risk factors compared with other approaches.For groups of risk factors, each risk factor's contribution was truncated at a lower limit of 0 because this is the lowest theoretical level of risk that can be attributable to a risk factor.PAFs were not calculated at the country level given the limited numbers of outcome events to perform these estimates after stratifying by country.Analyses were conducted using Stata (StataCorp) and R software.

BASELINE CHARACTERISTICS OF THE STUDY GROUP.
We enrolled 15,761 participants from Malaysia and

DISCUSSION
We report the rates of all-cause mortality and CVD and describe their characteristics and risk factors in 2 countries in Southeast Asia.More than 50% of mortality in the cohort resulted from CVD and cancer, with CVD causing 3 times more mortality events than cancer.This finding emphasizes the dominant role of noncommunicable diseases in driving adult mortality in the region, among both women and men.
We found significant differences between Malaysia and the Philippines.CVD caused a staggering 58% of mortality in the Philippines (with particularly high rates of stroke), whereas CVD was the cause of only 36% of mortality in Malaysia.Although the burden of CVD was higher in the Philippines, the rates of allcause mortality were higher in Malaysia, largely driven by higher rates of infections, injury, and respiratory causes in Malaysia.However, CVD and cancer together caused 50% or more mortality in both countries.Our estimates of causes of mortality are similar to estimates from vital statistics in Malaysia and the Philippines. 1,14There are important differences in risk factors between the 2 countries that could account for some of the differences in mortality patterns.For instance, Filipino households had higher rates of abdominal obesity and solid fuel use compared with Malaysian households, and this difference could lead to increased CVD mortality.Mortality, CVD, and Risk Factors in Southeast Asia Conversely, the higher all-cause mortality rates in Malaysian participants may be driven by lower educational attainment in participants from Malaysia compared with Filipino participants.Education has been shown to have a strong causal effect on mortality, and it was the largest risk factor for mortality (18.4% of the PAF) in our analysis. 15The benefits of education likely accrue through various pathways, ranging from economic and psychosocial to improved health behaviors. 16Improved health behaviors may account for up to one-third of the effect of education on health. 17proved nutrition and cognitive and noncognitive skill development are other possible pathways mediating the effect of education on health.However, the effects of education on health vary substantially across time and geographies, and much work remains to be done in understanding the precise mechanisms by which education affects health outcomes. 18In addition, there is likely some residual confounding in the estimate of education's effect on mortality, especially from difficult to measure early life deprivations such as stunting and childhood disease burden. 19It is notable that Malaysian participants had higher rates of all-cause mortality despite being wealthier than participants from the Philippines.We have previously shown that education is a stronger marker for mortality than wealth, a finding underscoring the importance of education in population health promotion vs policies focused solely on wealth creation. 8 found that compared with women, men had nearly twice the rate of all-cause mortality and CVD events.1][22] The exceptionally low rates of current smoking among women in our sample (3%, compared with 33% in men) and the high educational attainment among women may explain some of this gap. 23pertension was the leading risk factor for CVD Tobacco was ranked sixth as a risk factor for CVD (9.4% of PAF), with hypertension contributing to more than twice the PAF for CVD compared with tobacco.In addition, hypertension had a higher contribution to PAF for mortality than tobacco (12.2% of PAF vs 9.7%).
Compared with diabetes, hypertension has a lower HR for all-cause mortality and CVD.However, the much higher prevalence of hypertension (47%, vs 14% for diabetes) leads to a larger PAF and populationwide impact of hypertension.Together, these findings underscore the importance of prevention and better management of hypertension as being central in efforts to decrease the burden of CVD and mortality in Malaysia and the Philippines.A model of care involving nonphysician health workers, primary care physicians, family, and the provision of free medications for hypertension previously showed that it led to 65% of patients attaining control of blood pressure (<140/90 mm Hg) in Malaysia. 24pertension is the leading contributor to PAF for CVD, a finding that was consistent with our global analysis and with other global data sources. 25Similarly, low education as the leading contributor to PAF for mortality was also consistent with our global analysis. 5In contrast, tobacco had a lower contribution to both CVD and mortality compared with our global analysis.A total of 15.1% of our cohort were current users of tobacco, significantly lower than rates in South Asia (23.5%),China (22.6%), and South America (20.6%). 20,21Despite these findings, it is crucial that Malaysia and the Philippines continue to also focus on preventing initiation of tobacco use, an approach that will have large benefits in preventing CVD and all-cause mortality.The incidence of cardiovascular disease (CVD) and all-cause mortality in Southeast Asia (Malaysia and the Philippines), as well as their key drivers.DM ¼ diabetes mellitus; HDL ¼ high-density lipoprotein; HTN ¼ hypertension; PAF ¼ population-attributable fraction.Mortality, CVD, and Risk Factors in Southeast Asia sample, which is predominantly accounted for by (77% of participants).Therefore, the PAF estimates may be less robust for the Philippines.With increased follow-up of our cohort, more reliable estimates for the Philippines can be obtained as more events accrue.Finally, some risk factors had a high rate of missing values (particularly cholesterol and depression) (Supplemental Methods, Supplemental Table 4).Although we used a robust method of multiple imputation for the primary analysis, consistent with other PURE regional papers, future studies should aim to reduce rates of missing values to allow for more precise estimation.
Given the marked variations in risk factors, CVD, and mortality rates from 2 neighboring countries in Southeast Asia, our data emphasize the importance of obtaining prospective data from each of the several large countries in the region such as Indonesia, Vietnam, Thailand, and Myanmar.

CONCLUSIONS
In Southeast Asia, CVD is the leading cause of allcause mortality in both women and men.Hypertension is the leading risk factor for CVD, whereas low education is the leading risk factor for mortality (Central Illustration).Reducing CVD and mortality in adults will require a focus on improving educational attainment and the food system, as well as targeted measures to improve metabolic risk factors such as hypertension and diabetes.Southeast Asia can provide necessary information on whether the rates of CVD and all-cause mortality vary, as well as region-specific data on their determinants.
TRANSLATIONAL OUTLOOK: In Southeast Asia, rates of CVD are higher than in the Philippines, whereas rates of all-cause mortality are higher in Malaysia, with important differences in risk factor profiles between the 2 countries.A focus on education will likely have the highest impact in reducing premature mortality in the region, whereas hypertension control should be the highest priority for reducing CVD.Our findings also underscore the importance of obtaining prospective countrywide data in the region, to inform health policies.
were recruited from 28 rural and 46 urban communities at 3 collaborating centres.Using prespecified guidelines, a sample of households from each community with at least 1 member aged between 35 and 70 years (and intending to reside at the current home for at least 4 years) was invited to participate in the study.PURE is broadly reflective of its participating countries with regard to population demographics and mortality rates. 4Eligible persons provided written informed consent, and the study was approved by local ethics committees at each site.A total of 20,272 individuals with at least 1 follow-up visit, enrolled since 2007, were included in the cohort.Follow-up events recorded until April 2023 were included in the analysis.

( 24 .
2% of PAF).Other metabolic risk factors (diabetes, non-HDL cholesterol, and abdominal obesity) collectively contributed to 31.3% of the PAF for CVD.These 4 risk factors accounted for >50% of the PAF for CVD.

FIGURE 2
FIGURE 2 PAF for Cardiovascular Events and All-Cause Mortality

FUNDING
SUPPORT AND AUTHOR DISCLOSURES ADDRESS FOR CORRESPONDENCE: Dr Aditya K. Khetan, Hamilton General Hospital, McMaster University, 237 Barton Street E, Box 8P, Hamilton, Ontario, Canada.E-mail: aditya.khetan@phri.ca.PERSPECTIVES COMPETENCY IN PATIENT CARE AND PROCEDURAL SKILLS: The burden of CVD, allcause mortality, and their determinants differs in various countries.Understanding these differences is essential in developing context-specific health policies.Prospective countrywide studies can document the incidence rates of CVD and all-cause mortality and can clarify the contribution of risk factors.A standardized cohort of participants from countries within

TABLE 1
Baseline Characteristics of the Study Participants Overall, by Sex, and Country Values are mean AE SD or n (%).HDL ¼ high-density lipoprotein; LDL ¼ low-density lipoprotein; PURE ¼ Prospective Urban Rural Epidemiology; WHR ¼ waist to hip ratio.

Table 3
), strong associations (ie, HR: $1.5) were observed for diabetes (HR: 1.86; 95% CI: 1.63-2.12),hypertension(HR:1.66; 95% CI: 1.46-1.89),andloweducation(HR: 1.74; 95% CI: 1.36-2.24).Smaller associations were seen for former and current smoking, abdominal obesity, and elevated triglycerides.Estimates for elevated non-HDL cholesterol, physical inactivity, poor-quality diet, low grip strength, and depression were directionally consistent with a higher CVD risk, but the CIs were wide.Approximately 41% of the PAF for all-cause mortality was related to modifiable risk factors.As a cluster, metabolic risk factors (diabetes, hypertension, non-HDL cholesterol, and abdominal obesity) contributed to approximately 29% of the PAF for 1 Major Causes of Mortality in the Southeast Asia Cohort The leading causes of death in the Southeast Asia cohort are shown in descending frequency.CVD ¼ cardiovascular disease; GI ¼ gastrointestinal.all-causemortality.Figure2Bsummarizes the PAFs for all-cause mortality related to individual risk factors.The largest PAFs for all-cause mortality were attributable to low education (18.4%), low strength (13.4%), hypertension (12.2%), diabetes (11.2%), tobacco use (9.7%), and low activity (7.3%).

TABLE 2
Age-and Sex-Standardized Incidence of All-Cause Mortality and Cardiovascular DiseaseValues are incidence rates (95% CI).Incidence rates are based on 1,000 person-years of follow-up.The number of events for each outcome and category is shown as n.Major cardiovascular events include cardiovascular mortality, myocardial infarction, stroke, or heart failure.

TABLE 3
Associations Among Modifiable Risk Factors, All-Cause Mortality, and CVD Prospective Urban Rural Epidemiology Study Southeast Asia Findings 26UDY LIMITATIONS.Our findings may not be generalizable to other countries in Southeast Asia that are not included in our study.However, these findings emphasize that data from 1 country cannot26Within our Philippine sample, the prevalence of low education (and other socioeconomic disadvantages) was lower than other areas of the country, and this may explain some of the disparity in educational status between the Philippines and Malaysia in our sample.PAF risk estimates reflect the prevalence of risk factors in our CENTRAL ILLUSTRATION : ASIA, VOL. 4, NO. 8, 2024 Mortality, CVD, and Risk Factors in Southeast Asia A U G U S T 2 0 2 4 : 6 2 4 -6 3 3 JACC